Watching mutations as they happen

Darwin never knew what a mutation was. He inferred that the hereditary material of a species could change, and that changes could be positively or negatively selected, but he knew nothing of the “central dogma” of molecular biology: genes make RNA make protein. Until Watson and Crick came along with their coy but memorable statement, “it has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material”, we did not know how information was stored in biological molecules, and therefore did not know how the content of the information could change.

DNA sequencing has given us a window on how genomes have changed over the course of evolution: we can see how the sequence of a gene varies in different species of yeast, or between chimpanzees and man (or even between Neandertals and man). More recently, we’ve been able to perform evolution experiments in a test tube and see how mutations accumulate as a species evolves. But all of this has been after the fact; though we can sometimes deduce when mutations happened, and in what order, we’re not exactly watching them in real time. But now, a new approach recently published in Current Biology (Elez et al. Seeing mutations in living cells Curr Biol.20 1432-7 PMID: 20674359) allows us to watch DNA mismatches in the act of turning into mutations.

The approach makes use of the fact that bacteria have a set of proteins that detect mismatches between the two strands of DNA as the DNA is copied. Bactera also have a clever method of telling the difference between the old strand of DNA (which is by definition the one with the correct sequence) and the new strand: the old strand is methylated, while the new strand doesn’t become methylated until several minutes after it’s made. So when a mismatch is detected, there’s a way to fix it; you cut the new strand to remove the mismatch and try again.

This is a great system but clearly it doesn’t always work. Sometimes the mismatches don’t get repaired before the next round of DNA replication. Once the mismatch has been copied, you have a mutation. This is because both the correct residue from the old strand, and the incorrect residue from the new strand are copied into complementary sequences. There is no mismatch any more, and no way for the cell to know that one of the copied sequences is incorrect.

Elez et al. wondered whether the mismatch-detecting proteins would still be stuck to the mismatch up until the time of copying. If so, you would be able to see the mutation as it was about to become irreparable. They made GFP-labeled versions of the mismatch repair proteins, which should create foci — little spots — of GFP-carrying proteins stuck to mismatched DNA.

Now, some of the mismatches that happen during replication get repaired, and others don’t. Do the GFP-labeled repair proteins detect the mismatches that are going to be repaired, or the ones that aren’t going to be repaired? Or both? You could make a good argument for any of these three hypotheses, and each possibility suggests a different correlation between number of foci, the error rate of the DNA polymerase, and the number of mutations that are repaired.

Elez et al. find that the number of foci they see is very small in “wild-type” cells (cells with a normal DNA polymerase proof-reading function and functional DNA repair) — only 0.45% of cells show any spots at all. The number of foci increases if you prevent mismatches from being repaired, and increases yet further if you increase the expected error rate of the DNA polymerase. If you were detecting mismatches that go on to be repaired, you would expect that preventing repair wouldn’t increase the total number of foci. So it seems that a mismatch that is going to be repaired is invisible using this technique. Perhaps a mismatch that gets repaired never has enough mismatch repair proteins binding to it to show up as a bright spot. What’s interesting, though, is that the spots disappear with exactly the timing you would expect if they are removed as the DNA carrying the spot undergoes replication. This is consistent with the idea that the mismatch repair proteins can no longer “see” the problem after DNA replication; there is no mismatch any longer, and nothing for them to bind to (see figure). The authors estimate that over 99% of the time the mismatch repair proteins “win the race” and repair errors before the second round of replication.

If the number of visible spots on the DNA is equivalent to the number of unrepaired mismatches, it should also be equivalent to the eventual mutation rate. The authors test this idea by (1) measuring the frequency of mutations that give rise to resistance to rifampicin — this is the result of small mutations in the rpoB gene, which the authors are using as a surrogate for small mutations in the rest of the genome; and (2) calculating the expected mutation rate in their “wild-type” cultures assuming that the bright spots do indeed represent nascent mutations. The rifampicin resistance rate from (1) is linear relative to the number of spots, as it should be if the spots are mutations in the making; and the estimate of mutation rate from (2) is similar to other estimates of mutation rates in such cultures. So it seems to be a reasonable hypothesis that the mismatches we can see are the ones that are going to survive to be mutations.

If we can now watch mutations happening, what can we learn about them? The first question Elez et al. asked was whether mutations are uniform across the cells in the population. If all the individual cells in the population have the same chance of a mismatch happening as they replicate their DNA, then the distribution of mutations (read: foci) across the individual cells will follow a Poisson distribution. In “wild-type” cells the number of foci is too small to be able to determine the fit with a Poisson distribution, but in cells with an increased mutation rate (because the DNA polymerase has impaired proofreading activity, or because error correction is blocked) the distribution of number of foci looks quite close to Poisson. This appears to rule out the idea that a few cells in the population mutate much more frequently than the rest. Future directions include asking whether mutation rate increases as growth slows due to lack of nutrients, and whether species that don’t use methylation to mark their old DNA as the “correct” strand have higher mutation rates by this measure. And extending the method to eukaryotes. I’m sure the Lahav lab can hardly wait.

Incidentally, the paper is from Miroslav Radman’s lab in Paris, and Andrew Murray is 2nd author. So the subtitle of this post should be “what Andrew did on sabbatical”. Welcome back, Andrew.